Top 10 DevOps Projects for Your Resume (Beginner to Advanced)

Vishvesh Patel — Sat, 18 Jul 2026 19:18:07 +0000

Ten hands-on DevOps projects that hiring managers actually want to see. Covers Docker, Kubernetes, Terraform, CI/CD, AWS, and monitoring with real code and clear learning outcomes for every level.

Originally published on www.devopslesson.com, hands-on DevOps tutorials and career guides.

Project 1: Containerize a Multi-Service Application

Level: Beginner
Skills: Docker, Docker Compose, Networking
Time: 3 to 5 hours

What you build

Take a real application with at least two components, a web server and a database, and containerize it with Docker and Docker Compose. A good choice is a simple to-do app with a Node.js or Python backend and PostgreSQL or MongoDB.

What to include

A well-written Dockerfile for the application (multi-stage build, non-root user)
A docker-compose.yml that defines the app and database services
A named volume for database persistence
A custom Docker network for service communication
Health checks on both containers
Environment variable configuration via .env files
A .dockerignore to keep images lean

What it demonstrates

You understand not just docker run but how to architect a multi-service application for containers, manage data persistence, handle secrets with env vars, and write a production-quality Dockerfile.

README tip

Include the architecture diagram (even a text-based one), the commands to run it locally, and an explanation of why you chose a multi-stage build.

Project 2: CI/CD Pipeline with GitHub Actions

Level: Beginner
Skills: GitHub Actions, Docker, CI/CD
Time: 4 to 6 hours

What you build

A GitHub Actions workflow that automatically tests, builds, and pushes a Docker image to a registry every time code is pushed to the main branch.

What to include

A workflow triggered on push to main and on pull requests
A test job that runs your unit tests
A build job (dependent on the test job passing) that builds the Docker image
A push step that sends the image to Docker Hub or GitHub Container Registry (GHCR)
Image tagging with the git commit SHA for traceability
Docker layer caching with cache-from: type=gha
Secrets for registry credentials (no credentials in YAML)
Branch protection rules requiring the CI check to pass before merging

What it demonstrates

You can build a real CI/CD pipeline that follows security best practices, uses job dependencies correctly, and produces traceable artifacts.

Project 3: Infrastructure as Code with Terraform on AWS

Level: Beginner to Intermediate
Skills: Terraform, AWS, VPC, EC2
Time: 5 to 8 hours

What you build

Use Terraform to provision a complete AWS environment from scratch: a VPC with public and private subnets, an EC2 instance in the public subnet, a security group with proper rules, and an S3 bucket for state storage.

What to include

A remote backend storing Terraform state in S3 with DynamoDB locking
A reusable VPC module with public/private subnets across 2+ availability zones
An EC2 instance with user-data to install and start your application
Security groups with least-privilege rules (no 0.0.0.0/0 on SSH)
Outputs exposing the instance public IP and VPC ID
A terraform.tfvars file for environment-specific values
A .gitignore for state files and sensitive data

What it demonstrates

You can write real Terraform beyond tutorials: remote state, modules, proper variable handling, and actual AWS resource creation. This project maps directly to what teams do every day.

Project 4: Deploy to Kubernetes with Helm

Level: Intermediate
Skills: Kubernetes, kubectl, Helm, Deployments, Services, Ingress
Time: 6 to 10 hours

What you build

Take the containerized app from Project 1 and deploy it to a local Kubernetes cluster (using kind or minikube), then to a real cloud-managed cluster (AWS EKS or GKE free tier).

What to include

Kubernetes manifests: Deployment, Service, ConfigMap, Secret, Ingress
A Helm chart wrapping all your manifests with templated values
Horizontal Pod Autoscaler based on CPU utilization
Resource requests and limits on all containers
Readiness and liveness probes
A values.yaml for dev and values-prod.yaml for production
Deployment rollout with kubectl rollout status validation

What it demonstrates

You understand the difference between writing Kubernetes YAML and packaging applications properly with Helm. HPA and probes show you understand production concerns, not just getting containers to run.

Project 5: End-to-End GitOps Pipeline

Level: Intermediate
Skills: GitOps, ArgoCD or Flux, Kubernetes, CI/CD
Time: 8 to 12 hours

What you build

Implement GitOps: a Git repository is the single source of truth for what is deployed. When you merge a change to the repo, ArgoCD automatically syncs the cluster to match. No kubectl apply in pipelines.

What to include

A separate GitOps repository that holds only Kubernetes manifests
An application repository with a CI pipeline that updates the image tag in the GitOps repo on successful build
ArgoCD installed in your cluster watching the GitOps repo
Auto-sync with self-healing (ArgoCD reverts manual kubectl changes)
An ApplicationSet for managing multiple environments
A README explaining the full flow: PR merge → CI builds image → manifest repo updated → ArgoCD detects change → cluster updated

What it demonstrates

GitOps is one of the fastest-growing practices in cloud-native. Knowing ArgoCD or Flux puts you ahead of most candidates.

Project 6: Full Observability Stack

Level: Intermediate
Skills: Prometheus, Grafana, Alertmanager, Loki, OpenTelemetry
Time: 8 to 12 hours

What you build

Deploy a complete observability stack for your application: metrics with Prometheus, dashboards with Grafana, log aggregation with Loki, and alerting with Alertmanager.

What to include

Prometheus configured to scrape your application metrics endpoint
A custom Grafana dashboard showing request rate, error rate, latency (RED metrics)
An Alertmanager rule that fires when error rate exceeds 5% for 5 minutes
Loki receiving structured JSON logs from your application
A Grafana LogQL query correlating logs with spikes in error metrics
A runbook document explaining what each alert means and how to respond

What it demonstrates

Most engineers can run a service. SREs and senior DevOps engineers can observe it. This project shows you understand the difference between a dashboard that looks impressive and one that helps you find and fix problems.

Project 7: Automated AWS Infrastructure with Terraform and CI/CD

Level: Intermediate to Advanced
Skills: Terraform, AWS, GitHub Actions, remote state, modules
Time: 10 to 15 hours

What you build

Combine Terraform and CI/CD: a pipeline that automatically runs terraform plan on pull requests (posting the plan as a PR comment) and terraform apply on merge to main.

What to include

A modular Terraform codebase: separate modules for VPC, compute, database, and IAM
GitHub Actions workflow using hashicorp/setup-terraform
terraform plan output posted as a PR comment using actions/github-script
terraform apply running only on merge to main
AWS credentials passed via OIDC (not static keys — this is the modern, safer approach)
Separate Terraform workspaces for dev and prod environments
A Checkov or tfsec security scan step in the pipeline

What it demonstrates

This project combines two high-demand skills: Terraform expertise and pipeline automation. The OIDC authentication (no static AWS access keys) shows you understand security best practices.

Project 8: Self-Healing Infrastructure with Auto Scaling

Level: Advanced
Skills: AWS, Terraform, Auto Scaling, Load Balancers, CloudWatch
Time: 10 to 15 hours

What you build

An AWS application that automatically scales up under load and scales down when traffic drops, with zero-downtime deployments and a health check that routes traffic away from unhealthy instances.

What to include

An Application Load Balancer with HTTPS (ACM certificate)
An Auto Scaling group with a launch template
Scale-out policy triggered by 70% average CPU
Scale-in policy triggered by 30% average CPU
CloudWatch dashboard for the ASG and ALB metrics
A rolling deployment strategy (new instances, health check, traffic shift, old instances terminated)
Everything provisioned with Terraform

What it demonstrates

You understand how production applications actually handle variable load. This project demonstrates cloud architecture skills that go beyond tutorials.

Project 9: Multi-Environment Kubernetes Platform

Level: Advanced
Skills: Kubernetes, Terraform, EKS, namespaces, RBAC, network policies
Time: 15 to 20 hours

What you build

A Kubernetes platform with separate namespaces for dev, staging, and production environments with proper RBAC so developers can deploy to dev/staging but not production, network policies isolating environments, and resource quotas.

What to include

AWS EKS cluster provisioned with Terraform (using the official EKS module)
Three namespaces: dev, staging, production
RBAC: developer role with deploy access to dev/staging, SRE role with full access
Network policies: pods in dev cannot communicate with pods in production
LimitRange and ResourceQuota on each namespace
Cluster Autoscaler for automatic node scaling
External Secrets Operator syncing secrets from AWS Secrets Manager
A CI/CD pipeline that promotes images from dev → staging → production with manual approval gates

What it demonstrates

Platform engineering skills. You are not just deploying applications, you are building the platform that other engineers deploy to. This is what senior DevOps and platform engineering roles actually require.

Project 10: Full-Stack DevOps Deployment

Level: Advanced
Skills: All of the above combined
Time: 20 to 30 hours

What you build

Everything, end to end. A microservices application (at least two services that communicate with each other), deployed to Kubernetes on AWS, provisioned with Terraform, deployed via GitOps, monitored with Prometheus and Grafana, with a CI/CD pipeline that goes from commit to production with all the right gates.

What to include

Two or more services (e.g. an API and a worker) in separate repositories
Terraform for all AWS infrastructure (VPC, EKS, RDS, ECR, Secrets Manager)
GitOps with ArgoCD for deployments
CI pipeline per service: test, build image, push to ECR, update GitOps repo
Prometheus and Grafana for metrics (using the Prometheus Operator Helm chart)
Loki for logs
Alertmanager rules with a Slack or email notification
HTTPS via cert-manager and Let's Encrypt
Documentation: architecture diagram, runbook, deployment guide

What it demonstrates

This is a portfolio centrepiece. It touches every skill on a DevOps job description. Done well, with thorough documentation and a clear README, this is the kind of project that gets interviews.

How to present projects on your resume

GitHub is your portfolio. Make every repository public. Write a README that covers:

What the project does (one paragraph)
Architecture diagram (tools like draw.io or Excalidraw are free)
Technologies used (bullet list)
Key decisions and why you made them
How to run it locally
What you would do differently with more time

Do not list tools. Show outcomes.

Weak: "Used Terraform, Docker, and Kubernetes"

Strong: "Provisioned a multi-environment AWS EKS platform with Terraform, reducing environment provisioning time from 3 hours of manual steps to under 10 minutes"

Keep it real. Recruiters and hiring managers have seen every cloud tutorial project. What stands out is evidence of problem-solving: something that broke, what you discovered, what you changed.

Where to start

If you are new to DevOps, start with Project 1. Build each project before moving to the next. Resist the urge to jump to Kubernetes before you are comfortable with Docker.

Use these resources to get the foundation right:

DEV Community: Vishvesh Patel

Top 10 DevOps Projects for Your Resume (Beginner to Advanced)

Project 1: Containerize a Multi-Service Application

Project 2: CI/CD Pipeline with GitHub Actions

Project 3: Infrastructure as Code with Terraform on AWS

Project 4: Deploy to Kubernetes with Helm

Project 5: End-to-End GitOps Pipeline

Project 6: Full Observability Stack

Project 7: Automated AWS Infrastructure with Terraform and CI/CD

Project 8: Self-Healing Infrastructure with Auto Scaling

Project 9: Multi-Environment Kubernetes Platform

Project 10: Full-Stack DevOps Deployment

How to present projects on your resume

Where to start